import argparse
import sys

sys.path.append("..")


parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)

parser.add_argument('--config', default='configs/baselines/awa2/ALE.yml',
                    help='path of the config file (training only)')
parser.add_argument('--data_root', default='E:datasets/', help='数据集根路径')
parser.add_argument('--data_dir', default='Animals_with_Attributes2', help='数据集根路径')
parser.add_argument('--dataset', default='AWA2', help='数据集')
parser.add_argument('--feature_type', default='origin', help='origin原始数据特征，')
parser.add_argument('--phase', default='train', help='训练阶段')
parser.add_argument('--image_extractor', default='resnet18', help='特征提取模型')

parser.add_argument('--epochs', type=int, default=1000, help='Training batch size')

parser.add_argument('--cv_dir', default='logs/', help='dir to save checkpoints and logs to')
parser.add_argument('--name', default='temp', help='Name of exp used to name models')

# Model parameters
parser.add_argument('--model', default='simple', help='simple')

# Hyperparameters
parser.add_argument('--workers', type=int, default=8, help="Number of workers")
parser.add_argument('--batch_size', type=int, default=512, help="Training batch size")
parser.add_argument('--lr', type=float, default=0.01, help="Learning rate")
parser.add_argument('--lrg', type=float, default=1e-3, help="Learning rate feature extractor")
parser.add_argument('--wd', type=float, default=5e-5, help="Weight decay")
parser.add_argument('--save_every', type=int, default=10000, help="Frequency of snapshots in epochs")
parser.add_argument('--eval_val_every', type=int, default=1, help="Frequency of eval in epochs")
parser.add_argument('--max_epochs', type=int, default=800, help="Max number of epochs")

## g超分辨率上采样系数
parser.add_argument("--upscale_factor", default=4, type=int, choices=[2, 4, 8],
                    help="super resolution upscale factor")